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Hi, I am sorry to trouble you for my problems.
I downloaded the whole project and try to test your KEGG pre-trained weight with only mouse bulk dataset but there was a error about the shape of the weight matrix.
I added "model.load_weights(model_path,by_name=True)" and found the following information:ValueError: Layer #19 (named "dense_1"), weight <tf.Variable 'dense_1/kernel:0' shape=(512, 512) dtype=float32, numpy=
array( ………………) > has shape (512, 512), but the saved weight has shape (1536, 512).
I wonder if the using of single-cell dataset the key to this problem or maybe your weight is not fit for the code here?
I have tried to trained one with only bulk dataset and it was ok to predict. Well...
It would be greatly appreciated if you could tell me more, thanks.
The text was updated successfully, but these errors were encountered:
Hi, I am sorry to trouble you for my problems.
I downloaded the whole project and try to test your KEGG pre-trained weight with only mouse bulk dataset but there was a error about the shape of the weight matrix.
I added "model.load_weights(model_path,by_name=True)" and found the following information:ValueError: Layer #19 (named "dense_1"), weight <tf.Variable 'dense_1/kernel:0' shape=(512, 512) dtype=float32, numpy=
array( ………………) > has shape (512, 512), but the saved weight has shape (1536, 512).
I wonder if the using of single-cell dataset the key to this problem or maybe your weight is not fit for the code here?
I have tried to trained one with only bulk dataset and it was ok to predict. Well...
It would be greatly appreciated if you could tell me more, thanks.
The text was updated successfully, but these errors were encountered: